Evaluation and Evolution of NAOnto – An Ontology for Personalized Diabetes Management for Native Americans
Evaluation and Evolution of NAOnto – An Ontology for Personalized Diabetes Management for Native Americans
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DOI：
10.1109/iccc54389.2021.9674339
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发表时间：
2021-12
期刊：
影响因子：
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通讯作者：
Vikram Pandey;Juan Li;Shadi Alian
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文献类型：
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作者：
Vikram Pandey;Juan Li;Shadi Alian
本体已被提出用于各种医疗保健领域，以表示和管理知识，集成异构数据，辅助自然语言处理，促进机器学习，并支持智能医疗决策。虽然有许多本体的定义，它们在现实世界中的应用是有限的，因为它们的质量是未知的。本体的质量直接决定了本体在现实应用中的使用和重用，这对于医学领域尤为重要。为了保证本体的质量，本体的评价应该采用一套全面系统的度量标准和方法。在这项工作中，我们研究了在医学领域的本体评价问题。具体来说，我们提出了评估框架，NAOnto，我们开发的本体论的个性化糖尿病管理的美洲原住民。该框架包括两个重要的评价部分，即核查和确认。我们采用软件质量标准度量来验证本体作为一个软件应用程序，而本体应用到真实的应用程序，以验证其包含的知识。基于评估结果，所提出的本体已经经历了一个积极的演变过程，以解决发现的问题/问题。该框架演示了如何本体评价可以在医疗保健领域，以确保本体的质量。
Ontology has been proposed to use in various healthcare domains to represent and manage knowledge, integrate heterogeneous data, assist natural language processing, facilitate machine learning, and support intelligent medical decisions. Although there are many ontologies defined, their adoption in real-world applications is limited, because their quality is unknown. The quality of the ontology directly determines its use and reuse in real-world applications, which is especially important for the medical domain. To assure its quality, an ontology should be evaluated with a set of comprehensive and systematic metrics and approaches. In this work, we studied the ontology evaluation problem in the medical domain. Specifically, we present the evaluation framework to evaluate, NAOnto, an ontology we developed for personalized diabetes management of Native Americans. The framework consists of two important parts of the evaluation, namely verification, and validation. We adopt software quality standard metrics to verify ontology as a software application while applying the ontology to real applications to validate its contained knowledge. Based on the evaluation results, the proposed ontology has gone through an active evolution process to address the discovered issues/problems. The proposed framework demonstrates how ontology evaluation can be practiced in the healthcare domain to assure the quality of ontologies.